The Healthy Worker Survivor Effect: Target Parameters and Target Populations.
The Healthy Worker Survivor Effect: Target Parameters and Target Populations.
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DOI：
10.1007/s40572-017-0156-x
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发表时间：
2017-09
影响因子：
7.9
通讯作者：
Eisen EA
中科院分区：
文献类型：
--
作者：
Brown DM;Picciotto S;Costello S;Neophytou AM;Izano MA;Ferguson JM;Eisen EA
我们提供了一个深入的讨论时变混杂和选择偏差机制，导致健康工人幸存者效应（HWSE）。在这篇早期综述的更新中，我们区分了统称为HWSE的机制和可能导致的统计偏差。这一讨论强调了在职业流行病学的任何研究问题中确定目标参数和目标人群的重要性。目标参数可以对应于假设的工作场所干预；我们探讨这些目标参数的真实值是否反映了暴露对结果的病因学影响，或者在更现实的环境中实施暴露限制的潜在影响。如果一个队列包括在随访开始前雇用的工人，则HWSE机制可以限制估计数对其他目标人群的可移植性。我们总结了最近应用g方法控制HWSE的出版物，重点关注其目标参数、目标人群和假设干预措施。
We offer an in-depth discussion of the time-varying confounding and selection bias mechanisms that give rise to the healthy worker survivor effect (HWSE). In this update of an earlier review, we distinguish between the mechanisms collectively known as the HWSE and the statistical bias that can result. This discussion highlights the importance of identifying both the target parameter and the target population for any research question in occupational epidemiology. Target parameters can correspond to hypothetical workplace interventions; we explore whether these target parameters’ true values reflect the etiologic effect of an exposure on an outcome or the potential impact of enforcing an exposure limit in a more realistic setting. If a cohort includes workers hired before the start of follow-up, HWSE mechanisms can limit the transportability of the estimates to other target populations. We summarize recent publications that applied g-methods to control for the HWSE, focusing on their target parameters, target populations, and hypothetical interventions.